Google Ventures

GV is Alphabet-backed but operates as an autonomous, returns-first multi-stage venture firm investing across technology and life sciences. It is especially active in AI-native, technically differentiated companies and combines long-duration capital with hands-on operating support, while maintaining strict discipline on valuation and price-to-value fit.

Evaluation weights

How much weight this firm places on each dimension. Totals 100%.

Team-led · 30%

Metrics

23%

Revenue, growth, and unit economics

Market

19%

Size, timing, and competitive landscape

Team

30%

Founder experience and execution ability

Product

28%

Differentiation and technical quality

Biased toward technically deep founders over purely commercial teams
Willing to invest early in frontier technology if the moat is real
More flexible on round leadership than many firms
Aggressive on category-defining opportunities but conservative on price

Pitch difficulty

How hard it is to get a meeting and close funding from this firm.

Funded / yr: 90Deals closed in a typical year.
Led / yr: 33Rounds led in the last 12 months.
Pitches / yr: ~8684Decks reviewed in a typical year.
Acceptance rate: 1.0%Share of pitches that get funded.

Estimated — public data is not fully disclosed.

Why it's hard

Top-tier brand attracts highly competitive deal flow
High bar for technical moat and founder quality
Invests across many sectors but only in companies with outsized market potential
Strict valuation discipline eliminates many otherwise attractive deals

GV sees high deal volume globally, invests over $1 billion annually, and has flexibility across stages and sectors, but it sets a high bar on founder quality, technical differentiation, market scale, and valuation discipline. The combination of brand access, multi-stage capital, and a returns-first mandate means it can choose from the best opportunities and walk away from overpriced deals.

Green flags

What drives a yes for this firm.

Exceptional founders with strong technical depth and ambition
Clear technical moat or step-change product advantage
Large, durable market with strong timing tailwinds
Attractive value-to-price ratio relative to stage and company quality
Potential for a long-term multi-stage relationship

Red flags

What kills deals and gets a fast no.

Pricing the round too aggressively relative to traction or stage
Presenting an AI story without real technical differentiation
Targeting a market that is too small or too short-lived for venture-scale returns
Lack of conviction in the founding team or weak founder-market fit
Later-stage metrics that do not support scalability, retention, or category leadership

How to win

Patterns that lead to successful pitches.

Lead with the founder's unique technical insight and why this team is uniquely suited to win
Show a non-obvious technical moat, not just strong positioning or branding
Frame the company as attacking a very large market with durable tailwinds, especially around AI or infrastructure shifts
Be explicit about why the current round price offers compelling upside relative to stage and traction
Demonstrate openness to a long-term, multi-stage partnership and use of GV's operating platform

Fund strategy & identity

Who they are and how they operate.

Invests across Seed, Series A, Series B, Series C, and Growth with flexible ownership targets
Backs companies across enterprise, consumer, frontier tech, fintech, and life sciences
Uses long-term, single-LP capital to support companies across multiple rounds
Applies hard valuation discipline, passing when price does not match stage, quality, or upside
Pairs capital with platform resources in design, engineering, marketing, and talent

Firm identity

Autonomous Alphabet-backed financial investorMulti-stage firm investing from Seed through GrowthTechnical-differentiation driven, especially in AI and frontier techLong-horizon partner operating in 'decades, not rounds'Flexible on leading vs. following if it gains access to the best companies

Investment focus

Industries, themes, and typical ARR expectations.

Industries

AI/MLEnterprise SoftwareDeveloper ToolsConsumer InternetOther / GenericFintechHealthcareBiotech & Life Sciences

Investment themes

AI-native software and infrastructureDeveloper tools and enterprise platformsFrontier compute, hardware, and photonicsHealthcare, life sciences, and data-driven clinical platformsFintech infrastructure and regulated-market disruptionConsumer platforms with network effects or exceptional product experience

Typical check by stage

Pre Seed$0.25M-$1M

Seed$1M-$5M

Series A$5M-$15M

Series B$10M-$30M

Series C$15M-$50M

Growth$30M-$100M+

Typical ARR by stage

Seed$0-$1M

Series A$1M-$5M

Series B$5M-$20M

Series C$20M-$50M

Growth$50M+

Investment thesis

Core beliefs and strategy behind their investing approach.

GV is a multi‑stage venture firm that invests across industries with a long‑term orientation—"decades, not rounds." Backed solely by Alphabet, the firm operates autonomously and is financially driven, able to back competitors to Google while giving portfolio companies access to Google talent and technology when useful. Its sector focus spans AI, enterprise, consumer, frontier technology, and life sciences, with roughly 80% of new investments classified as AI‑native. GV maintains a strong life‑sciences practice and looks for ideas that require deep technical differentiation and long‑term capital support. Geographically, GV backs startups in North America, Europe, and Israel, with a dedicated European hub in London and over $1 billion invested in European startups since 2014. The firm’s core belief is that value is created by combining founder empathy, hands‑on company‑building resources (design, engineering, marketing, talent) with selective access to Google’s network. GV targets opportunities that demand multi‑stage relationships and technical moats, while discarding deals where the price does not reflect stage or quality. The firm positions itself as a returns‑first investor rather than a strategic corporate arm, aiming to be a partner of choice irrespective of the eventual acquirer.

Decision patterns

How they evaluate and make investment decisions.

GV places founder quality and technical differentiation at the top of its checklist, weighing market size and timing second, and scrutinizing valuation and price‑to‑value ratio as a hard constraint. Tom Hulme emphasizes that the firm invests purely for financial return and is "relaxed" about leading versus joining syndicates, preferring entry into the best companies over ownership rules. The firm passes on AI deals when the value‑to‑price ratio does not work. Internally, partners are empowered to make convictions with few internal blocks; David Krane notes they invest over a billion dollars a year with high volume. Relationship‑driven conviction is evident in examples like the $10 M Series A in Universe, where GV’s partner joined the board. Early‑stage decisions heavily weight team and product potential, while later stages incorporate traction and scalability, but price discipline remains pivotal. GV favors large, durable markets where AI or other frontier tech creates step‑change opportunities and avoids overpaying when stage, price, or quality misalign.

Risk appetite

GV exhibits a high‑conviction, flexible risk appetite. It is comfortable backing ultra‑early, pre‑revenue life‑science or frontier‑tech ideas as well as writing massive growth checks (e.g., the $257.79 M Uber round). The firm frequently leads seed and Series A rounds but will co‑lead or follow when that maximizes access and outcomes. Its patient‑capital model—backed by a single LP and a long‑term horizon—allows it to take on risk, yet partners stress valuation discipline, explicitly walking away from deals where price does not align with stage or quality. Overall, GV is aggressive in technology bets (especially AI) but remains conservative on pricing, balancing bold platform investments with rigorous value‑to‑price assessment.

Notable investments

Key portfolio companies and why they fit the thesis.

Blue Water AutonomyLead
Frontier defense autonomy leveraging AI perception aligns with GV's AI and frontier-tech conviction. GV led the Series A (Dave Munichiello).
Mechanical OrchardLead
Enterprise modernization platform with AI-forward software migration. GV led the $50M Series B.
MetaviewLead
AI-native hiring platform. GV led the $35M Series B.
ComplyanceLead
Agentic AI for governance, risk and compliance. GV led the $20M Series A (Feb 2026).
SambaNovaLead
AI infrastructure and hardware venture. GV co-led the 2018 $56M Series A with Walden International.
EpiBiologicsLead
Novel extracellular protein degradation platform aligns with GV's life-sciences investment theme.
AttioLead
AI-native CRM; GV led Attio's $52M Series B (Aug 2025).
DriverLead
AI-driven technical documentation tool accelerates enterprise productivity, fitting GV's AI tooling thesis.
TranslucentLead
AI applied to healthcare finance. GV led the $27M Series A (March 2026).
Guild.aiLead
Collaborative intelligence platform aligns with GV's AI apps and developer-tools investment theses.

Co-invested with

Other firms in this catalog who've backed the same companies.

No catalog overlap found yet. Co-investors are derived from each firm's notable investments — connections may surface as more firms are added.

Partners

General Partner

Google Ventures

GV general partner focused on AI and enterprise investments.

AIEarly-stage startupsEnterprise softwareGrowth-stage startups

Frederique Dame

General Partner

Google Ventures

General Partner at GV investing across consumer, AI, life sciences, and women’s health after product leadership roles at Uber and Yahoo.

AIConsumerGrowthLife SciencesSeed / Early StageWomen's health

David Schenkein, MD

General Partner

Associate

Google Ventures

New York-based GV associate focused on AI investments.

AIEnterprise softwareFinTechGrowth stageSeed stage

Public voice

Notable statements and public positions.

“GV operates on long time horizons and deals in decades, not rounds.”
“Our partnership conversations center not around deals or funding rounds, but around the highest‑potential humans we meet each week. We seek out the most curious and impactful people across tech – and then build long‑lasting relationships of trust and respect.”
“No question: we’re early… This is a pitch clock that we’ve never seen before. This game is moving incredibly quickly, for better and for worse.”

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